Yousef Tarek Nathan — AI & Data Science Developer

Machine Learning

Heart Disease Prediction

Machine learning project for analyzing clinical data and predicting the presence of heart disease using data preprocessing, exploratory analysis, and classification techniques.

TECHNOLOGIES

Python · Pandas · NumPy · Scikit-learn · Jupyter Notebook

PROBLEM

Predict the presence of heart disease from clinical and patient-related features using machine learning.

APPROACH

Preprocess and explore the clinical dataset, prepare relevant features, train classification models, and evaluate their performance for heart disease prediction.

DATASET

Clinical dataset containing patient-related features used to train and evaluate heart disease classification models.

IMPLEMENTATION

Data preprocessing, exploratory data analysis, feature analysis, model training, and classification evaluation using Scikit-learn.

RESULTS

Evaluated machine learning classification models for heart disease prediction using standard performance metrics.

KEY INSIGHTS

Compared machine learning classification approaches and analyzed model performance using evaluation metrics to identify patterns associated with heart disease.

Yousef Tarek Nathan

AI & Data Science Developer